ODT: Optimal deadline-based trajectory for mobile sinks in WSN: A decision tree and dynamic programming approach

In this paper, an adaptive path construction approach for Mobile Sink (MS) in wireless sensor networks (WSNs) for data gathering has been proposed. The path is constructed based on selecting Rendezvous Points (RPs) in the sensing field where the MS stops in order to collect the data. Compared with the most existing RP-based schemes, which rely on fixed RPs to construct the path where these points will stay fixed during the whole network lifetime, we propose an adaptive path construction where the locations of the RPs are dynamically updated using a Fuzzy Inference System (FIS). The proposed FIS, which is named Fuzzy_RPs, has three inputs and one output. The inputs are: the remaining energy of the sensor nodes, the transmission distance between the RPs and the sensor nodes, and the number of surrounding neighbors of each node. The output of FIS is a weight value for each sensor node generated based on the previous three parameters and, thus, each RP is updated to its new location accordingly. Simulation results have shown that the proposed approach extends the network lifetime compared with another existing approach that uses fixed RPs. For example, in terms of using the first dead node as a metric for the network lifetime, when the number of deployed sensor nodes changes from 150 to 300, an improvement that ranges from 48.3% to 83.76% has been achieved compared with another related approach that uses fixed RPs.

Wireless sensor networks (WSN) consist of large number of sensor nodes. These small and low cost sensor nodes are deployed in monitoring region of interest. Since sensors perform multiple functions such as data gathering and data transmission results in energy depletion, these effects the network lifetime. The nodes having tendency to fail due to energy depletion is the critical issue in WSN. Due to wide number of applications of WSN, it is required to enhance the life time of entire network. Proposed method in this paper is aimed to optimize the energy dissipation by modifying the CH (Cluster Head) selection approach in LEACH (Low Energy Adaptive Clustering Hierarchy) algorithm and avoids the energy-hole problem considering mobility to the sink node which helps to prolong the lifetime of entire network.

In wireless sensor networks (WSNs) localization systems are required to provide position information of sensor nodes. Position information of sensor nodes with unknown physical positions is acquired with the help of beacons or anchors. Beacon placement is one of the prominent factors that shape the localization performance in sensor networks. Placing more beacons in a network is generally not a cost-effective idea. However, a carefully designed technique can increase the accuracy by placing a limited number of beacons. This paper presents a requirement based beacon placement algorithm to optimize number of beacons to cover the entire WSN. A novel algorithm for routing towards the mobile sink is also proposed, which utilizes the beacon nodes more than sensor nodes to route data towards a mobile sink. This strategy helps to reduce the energy consumption of the WSN and increase the network lifetime. Simulation result shows that the proposed beacon placement scheme is effective in a sensor network with high node density and also evaluates the proposed routing algorithm.

Energy efficiency is a major factor in designing wireless sensor networks (WSNs). Clustering design and grid‐based scheme are one of the techniques to save energy in WSNs. However, for a mobile sink in WSNs, packet loss rate that occurs due to the sink mobility is also a significant challenge. Here, an enhanced routing‐G i protocol for a mobile sink in WSNs has been proposed to not only enhance energy efficiency but also minimise the packet loss rate. Simulation results show that the proposed protocol is more efficient than the previous protocols in terms of the network lifespan, energy efficiency, and packet delivery ratio. Thus, the proposed approach in this work could further be adapted to investigate highly mobility of sink in WSNs.

The advantages of deploying mobile sinks (MSs) in wireless sensor networks (WSNs) have attracted tremendous attention recently, because mobility of a sink provides an efficient method to improve data gathering performance in WSNs. However, in such kind of WSN, the efficiency of data dissemination is obviously affected by the trajectory of the MS. Therefore, optimal moving schemes of the MS have been studied in many researches. Nevertheless, in many cases, the trajectory of the MS is not able to change ideally as previous studies assumed but depending on the environmental conditions. In this paper, we focus on the efficiency of data gathering in WSN with a MS whose trajectory cannot change ideally and propose a new data diffusion scheme - implementing a new Pre-Diffusion Algorithm (PDA) in a hierarchical WSN aimed at improving data gathering efficiency. This hierarchical WSN is composed of several clusters, and datatransmission is done by higher powered cluster head (CH) node. Our scheme predetermines the cluster area where the MS is going to arrive in most probability in next period of time. MS fulfills data converging in the cluster head (CH)whose distance to the MS may the smallest compared with other CHs when data gathering starts. Thus more data can be collected with less trajectory length of MS. Simulation results show that our proposed scheme improves data gathering efficiency as compared to conventional scheme.

Maximization of lifetime of wireless sensor network (WSN) is an emerging area of research in present scenario. Many authors are performing their research work, so that they could achieve lower energy consumption for the sensor network which leads to increase in lifetime of network. Our work focuses on sink mobility in a fixed trajectory within a wireless sensor network while sensed data are required to be collected. We divide the whole sensor network into two different regions as direct communication area (DCA) and multi-hop communication area (MCA). Sensors node that lies in DCA is at one hop count distance from the sink node trajectory while sensors within MCA are at more than one hop count from the trajectory. We considered all the sensors that are within DCA as subsink nodes. During sink mobility, whenever a subsink is closer to the mobile sink node, then it starts transmitting its data to the sink node. But those sensors that are within MCA needs to search an appropriate sink node for sending its sensed data to the subsink so that on further stage, that subsink could provide those data to the sink node whenever it is in nearest proximity of that subsink. Basically, a sink node is the ultimate destination for the data while a subsink node acts as a relay node for the nodes that are within MCA. So our work is to find out the appropriate subsink node from a given set of subsinks. For doing so, we used location-aided routing on global positioning system (GPS)-enabled sensors and sink node. Our work is validated through simulation experiments using NS-2.

Division of the entire wireless sensor network geographic area into number of equal sized regions by applying virtual grid and strategy to appoint head node of the cluster in each region improves stability, consistency, and lifetime of the wireless sensor network. Applying the same size of grid to the different size of wireless sensor networks will not give consistent performance. In this paper, we are presenting a protocol which will dynamically determine the size of the virtual grid, which will give optimal performance of any geographic sized wireless sensor network. The protocol also allows to place sink node to any location and not at some fixed specific location. Protocol discussed in this paper can also support multiple sink nodes. Protocol dynamically takes decision to transmit the data directly to the sink node or by using multi-hop transmission by considering distances between sensor nodes internally and sink node(s), which will optimize energy efficiency of the sensor nodes and increases the lifetime of wireless sensor network.

This paper exploits sink mobility to prolong the network lifetime in wireless sensor networks where the information delay caused by moving the sink should be bounded. Due to the combinational complexity of this problem, most previous proposals focus on heuristics and provable optimal algorithms remain unknown. In this paper, we build a unified framework for analyzing this joint sink mobility, routing, delay, and so on. We discuss the induced subproblems and present efficient solutions for them. Then, we generalize these solutions and propose a polynomial-time optimal algorithm for the origin problem. In simulations, we show the benefits of involving a mobile sink and the impact of network parameters (e.g., the number of sensors, the delay bound, etc.) on the network lifetime. Furthermore, we study the effects of different trajectories of the sink and provide important insights for designing mobility schemes in real-world mobile WNNs.

A wireless sensor network (WSN) consists of a large number of interconnected sensors, which provides unique features to visualize the real world scenario. It explores many opportunities in the field of research due to its wide range of applications in current fields that require survey and periodic monitoring which is inevitable in our daily life. However, the main limitations of such sensors are their resource constrained nature, mainly to conserve battery power for extending the network lifetime. We have proposed an algorithm for energy efficiency in WSN in which mobile sink node is used to operate the routing process considering the shortest path between multiple unequal clusters with reduced energy. This model also ensures non-occurrences of energy hole problems within the network area.

In wireless sensor networks (WSNs), sensor nodes near static sink will have more traffic load to forward and the network lifetime will get largely reduced. This problem is referred to as the hotspot problem. Recently, adopting sink mobility has been considered as a good strategy to overcome the hotspot problem. Despite its many advantages, due to the dynamic network topology caused by sink mobility, data transmission to the mobile sink is a challenging task. To achieve efficient data dissemination, nodes need to reconstruct their routes toward the latest location of the mobile sink, which weakens the energy conservation aim. In this paper, we proposed an energy-efficient cluster-based dynamic routes adjustment approach (EECDRA) which aims to minimize the routes reconstruction cost of the sensor nodes while maintaining nearly optimal routes to the latest location of the mobile sinks. The network is divided into several equal clusters and cluster heads are selected within each cluster. We also set some communication rules that manage routes reconstruction process accordingly requiring only a limited number of nodes to readjust their data delivery routes toward the mobile sinks. Simulation results show that the mobile sinks for reducing reconstruction of route have improved the energy efficiency and prolonged lifetime of wireless sensor network.

Wireless sensor networks (WSNs) are formed using a cluster of sensor nodes (SNs), deployed randomly to perform sensing operations in an area under observation. Due to the unavailability of an external power source, the energy efficiency considered as one of the critical issues in WSNs. Selection of a sensor node (SN) from a wireless sensor network (WSN) cluster to serve as an aggregator or cluster head (CH), considered as an efficient method to increase the lifetime of wireless sensor network (WSN). In this paper, we have proposed an energy efficient CH selection scheme for WSN, to enhance the lifetime and average residual energy of a single WSN cluster. The proposed strategy nominates a group SNs as CHs, based on their channel condition with the base station (BS) and their residual energy. The proposed algorithm is helpful in solving the problem of unbalanced energy consumption in WSNs. Furthermore, the mechanism of using mobile sink during the hand-off stage helps to overcome the delay in data transmission. Moreover, the incorporation of energy harvesting significantly increases the lifetime of WSN. In comparison to a state-of-art technique available in the literature, our scheme shows a 33% increase in lifetime and presents a steady decrease in residual energy for the same rounds of data transmission.

Numerous research works have shown that Wireless Sensor Network (WSN) plays an important role in enabling technology. It has been applied in fields such as agribusiness. The concept of mobile sinks in WSN is to resolve the multihop routing issues of inefficient data collection. This paper uses the Air-Ground Collaborative Wireless Network (AGCWN) mobility models and proposes a Data Store-and-Delivery algorithm with an approach, called Center Tractor Scanning (CTS) that maximizes buffer utilization and battery capacity in data collection. Simulation results show mobile sinks using CTS collect more data per trip as compare to other existing approaches. This study also highlights the importance of maximizing the buffer utilization and battery capacity of mobile sinks, thus improve the efficiency of data collection for WSN.

Wireless Sensor Networks (WSNs) have led to tremendous growth in the development of sensor technology and offer numerous applications, such as wildlife monitoring, environment, healthcare, military surveillance and security systems. In terms of performance, the evolutions of WSN routing protocols play a vital role in extending the lifetime of networking operations. Due to the limited resources of power in sensor nodes, the design and implementation of an energy-efficient routing protocol comprise a key challenge for researchers. Before, in the case of a static sink, nodes at farther areas from the sink transmit their sensed data at a longer transmission range and die early, while nearby nodes face lesser transmission costs and stay alive for a longer period. This unbalanced energy distribution creates energy holes in ares far from the sink in WSNs. Mobility-based sink routing protocols are proposed to minimize the sub-optimal energy consumption in WSNs, as the sink mobility covers the sensor field, which alleviates the overall load-balancing among sensor nodes. In order to overcome the energy hole issue while prolonging the network lifetime, it is important to determine the optimal mobility pattern. In this regard, we propose the Spiral Mobility based on Optimized Clustering (SMOC) routing protocol and the Multiple sink-based SMOC (M-SMOC) routing protocol for large-scale WSNs. Performance evaluations of the proposed protocols are compared with various existing routing protocols based on static sink, random mobility and grid mobility. Different numbers of performance parameters are considered for evaluation, such as network lifetime, network stability, packet drop ratio, packet delivery ratio, end-to-end delay, average energy consumption, network connection time and the impact of different heterogeneity levels. Experimental results show the benefits of the spiral mobility pattern and how it improves the network lifetime and stability period over the existing state-of-the-art routing protocols.

Limited energy supply (battery-powered) is a crucial problem in wireless sensor networks (WSNs). Sensor node placement schemes and routing protocols are mostly proposed to address this problem. In this paper, we first present how to place sensor nodes by use of a minimal number of them to maximize the coverage area when the communication radius of the sensor node is different from the sensing radius, which results in the application of regular topology to WSNs deployment. With nodes placed at an equal distance and equipped with an equal power supply, the problem of unbalanced energy consumption in 2-D regular topologies becomes more severe and much more difficult to tackle than that in 1-D chains, though the latter is known as an already quite hard problem. We address this problem and propose an adaptive data collection scheme by employing different communication radii for nodes in different locations to balance the energy consumption in WSNs. In order to achieve the ultimate goal of maximizing network lifetime in grid-based WSNs, we give a mathematical formulation, which shows the problem of maximizing network lifetime is a nonlinear programming problem and NP-hard even in the 1-D case. We discuss several heuristic solutions and show that the halving shift data collection scheme is the best solution among them. We also generalize the maximizing network lifetime problem to the randomly-deployed WSNs, which shows the significance of our mathematical formulation for this crucial problem in WSNs.

Wireless sensor networks with the mobile sink can help to prevent the hot-spot problem and improve the network lifetime. However, in practice, the trajectories of the sink can not ideally change due to the obstacle of the environment or the requirement of the application. The constraint on trajectory of the mobile sink causes the different connection time between the mobile sink and the sensor node, which might result in the imbalance depletion of energy. We propose here an efficient data gathering policy to jointly consider the constrained mobility of the sink and the different connection time at the sensor node. The policy increases the network lifetime in wireless sensor networks with path-constrained mobile sink by optimizing the assignment sensor node. In addition, we also propose the policy to cope with the overlapped connection time of the sink and sensor node due to the movement of the sink. The simulation results demonstrate the effectiveness of the proposed policy: by carefully considering the trajectory of the sink and effectively assigning the sensor node, the network lifetime is increased.